This ComfyUI tutorial workflow shows how to upscale a single image using SeedVR2 7B Int8, a one-step diffusion model trained with adversarial objectives and adaptive window attention. Instead of iterative sampling, SeedVR2 performs a single forward pass to enhance resolution and restore detail, making it fast and consistent. The Int8 quantized weights reduce memory usage while preserving most of the model’s fidelity, which is helpful on mid-range GPUs.
Technically, the graph is straightforward: LoadImage feeds your source into the SeedVR2 7B Int8 node (ID: 1970dcb4-982a-4c01-a373-4d239a3041e4), which wraps the SeedVR2 checkpoint and its paired VAE (seedvr2_ema_vae_fp16.safetensors). The model outputs an upscaled image in a single step, which you can preview with ImageCompare (original vs upscaled) and then export via SaveImage. A MarkdownNote in the graph provides quick tips and references. Because it’s a one-step diffusion upscaler, you don’t need to tune sampler steps or schedulers—just set your desired output size (or keep defaults), run, and review.
API
코드에서 이 워크플로우 사용하기
모든 Comfy 워크플로우는 JSON 그래프입니다. 아래 페이로드는 이 워크플로우 그 자체로, ComfyUI에서 실행되는 것과 동일합니다 — URL에서 가져오거나, 버전 관리에 보관하거나, ComfyUI에서 불러와 노드별로 실행할 수 있습니다.
Comfy SDK로 TypeScript 또는 Python에서 실행하세요. 동일한 코드는 Comfy Cloud 또는 직접 호스팅하는 ComfyUI 모두에 적용됩니다 — 기본 URL만 다릅니다.
// Install (beta)
npm i @comfyorg/sdk
// Run this workflow (TypeScript)
import { Comfy } from "@comfyorg/sdk";
const client = new Comfy({ apiKey: "comfyui-..." });
const wf = await client.workflows.fromFile("workflow_api.json");
const job = await client.run(wf);
await job.getOutputs("<output-node-id>")[0].toFile("output.png");SDK는 API 형식의 워크플로우를 사용합니다: 이 워크플로우를 ComfyUI에서 열고 파일 → 워크플로우 내보내기(API)를 사용하세요.
